The Assembly Audio Transcription allows for accurate transcription of audio into text. Utilizing advanced voice recognition technologies, the AI analyzes and converts voice recordings into text, facilitating content analysis and accessibility. Additionally, on Tess AI, it is possible to use the results of the literal transcription to process with other AI models and prepare summaries, meeting minutes, gain insights, and conduct strategic analyses.
Fields to Fill
- Audio Upload: Upload the audio file you wish to transcribe.
- Audio Language: Specify the language spoken in the audio to optimize transcription accuracy. In this field, you can leave the language option as 'auto' so that the AI identifies the audio, and the user does not need to specify the language for each audio file.
Output Result
The transcribed text will be presented in a readable format, providing a literal transcription.
Use Cases
- Documentation of Meetings and Conferences: Automatically transcribe discussions from meetings and conferences to create detailed written records, facilitating the tracking of actions and decisions. With the application of AI, you can prepare meeting minutes and structure documents with the results of the transcriptions.
- Interview Analysis: Convert recorded interviews into text for qualitative analysis, allowing for easier evaluation of themes and patterns. Additionally, prepare feedback emails using AI combined with the transcription.
- Education and Online Learning: Transform lectures, podcasts, and recorded classes into text for use in study materials and e-learning platforms. Also, prepare summaries, articles, and mind maps to facilitate the learning process, all with the application of AI.
Limitations
- The file size must be up to 200MB for files uploaded via input and 5GB for cloud files via link.
- The file must be in the following formats: mp4, m4p (with DRM), m4v, mxf, mp2, mov, mts, m2ts, ts, webm, 3ga, aac, ac3, 8svx, aif, aiff, alac, amr, ape, au, dss, flac, flv, m4a, m4b, m4p, m4r, mp3, mpga, ogg, oga, mogg, opus, qcp, tta, voc, wav, wma, and wv.
Conclusion
The Assembly Audio Transcription function offers an efficient and accurate solution for converting audio into text, making it essential for organizations seeking to improve information management and accessibility of voice-based content. With transcription, AI models can be trained to generate meeting minutes, conduct sentiment analysis of conversations, create summaries, and more.